Differences in evolutionary accessibility determine which equally effective regulatory motif evolves to generate pulses

Author:

Xiong Kun12ORCID,Gerstein Mark2345ORCID,Masel Joanna6ORCID

Affiliation:

1. Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ 85721, USA

2. Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA

3. Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA

4. Department of Computer Science, Yale University, New Haven, CT 06520, USA

5. Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA

6. Department of Ecology and Evolutionary Biology, University of Arizona, Tucson,AZ 85721, USA

Abstract

Abstract Transcriptional regulatory networks (TRNs) are enriched for certain “motifs.” Motif usage is commonly interpreted in adaptationist terms, i.e., that the optimal motif evolves. But certain motifs can also evolve more easily than others. Here, we computationally evolved TRNs to produce a pulse of an effector protein. Two well-known motifs, type 1 incoherent feed-forward loops (I1FFLs) and negative feedback loops (NFBLs), evolved as the primary solutions. The relative rates at which these two motifs evolve depend on selection conditions, but under all conditions, either motif achieves similar performance. I1FFLs generally evolve more often than NFBLs. Selection for a tall pulse favors NFBLs, while selection for a fast response favors I1FFLs. I1FFLs are more evolutionarily accessible early on, before the effector protein evolves high expression; when NFBLs subsequently evolve, they tend to do so from a conjugated I1FFL-NFBL genotype. In the empirical S. cerevisiae TRN, output genes of NFBLs had higher expression levels than those of I1FFLs. These results suggest that evolutionary accessibility, and not relative functionality, shapes which motifs evolve in TRNs, and does so as a function of the expression levels of particular genes.

Funder

University of Arizona and by the National Science Foundation

Williams Professorship fund

Publisher

Oxford University Press (OUP)

Subject

Genetics

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